Cookie Consent

This site uses cookies for functionality. To see our cookie policy click here.

If you continue to use this site we will assume that you are happy with this.

Aviation ingests a huge
Black Swan Mar/Apr 2020 Download PDF

Cloud Image

The term “Black Swan” was popularised by the philosopher/financial trader/statistician/polymath Nicholas Taleb* to describe an unpredicted event that has catastrophic consequences. From ancient times to the 1600s all swans were assumed to be white and the term “rare as a black swan” was used to describe an extremely improbable or impossible happening; then Europeans started to explore Australia and discovered that there were indeed black swans.

Taleb observed that Black Swan events are not only unpredictable and improbable but they are also inevitable. In fact, the 30-year chart shows four major Black Swan events impacting the aviation industry.

Predicting such specific events may be impossible, but, Taleb argues, it is necessary to prepare for catastrophes. Taleb himself made a fortune from the Financial Crash by consistently maintaining a portfolio of stocks. bonds and options, most of which were designed for returns in normal times but significant portion of which was specifically designed to pay out in an extreme event. He is, admittedly, a bit vague as to how to apply this technique outside the financial markets.

According to Taleb, people, especially specialist forecasters, are psychologically very poor at accepting the inevitability of Black Swans and preparing for them. He is particularly scathing about standard forecasting, which he sees as little more than a projection of “normal” times, with false security provided by statistical techniques that are useless in open-ended environments. Normal distributions, bell curves and standard deviations, for example, were originally designed for measuring human characteristics like height, longevity, etc — a closed environment — but are inappropriately used in forecasting in complex open environments. The confidence levels forecast — to 90%, 95% or even 99% certainties — are meaningless. Taleb is probably being unfair to mainstream statisticians and forecasters, but he does have a point about how easy it is to be complacent when all seems to be going well — the Great Moderation that preceded the Global Financial Crash, for example. Taleb uses the analogy of a semi-intelligent turkey who predicts its contented future based on its experience of being carefully looked after and well fed every day, blissfully unaware that this is the lead-up to Christmas.

In a typical twist, in order to make sure no one can fully follow his constantly evolving ideas, Taleb is now saying that Covid-19 is closer to being a White than a Black Swan as the potential risk of a pandemic in an ever more closely interconnected world was or should have been well known.

Maybe; but the impact of Covid-19 on the aviation business is genuinely unprecedented. As the graphs highlight, global air traffic, measured in RPKs, has just fallen off the cliff. By contrast, the previous Black Swan events — Gulf War 1, September 11, and the Global Financial Crisis — look like relatively minor blips in the long-term traffic pattern. Covid-19 is unprecedented in its global impact: all regions have been severely affected whereas Asian traffic stood up well to both September 11 and the Financial Crisis. It is also unprecedented in the duration of its impact: airline executives recall global traffic falling by a third after September 11 or even after the SARS outbreak in Asia in 2003, but in both cases this decline was only for a few weeks before it started to recover. The full impact of the enforced grounding of aircraft by governments, because of Covid-19, is going to last for two quarters of this year at least.

IATA’s late-March prediction for global RPKs in 2020 was -38%. We have taken this figure though it is already starting to look a bit optimistic. IATA’s traffic forecast was predicated on the assumed reductions in airline capacity shown in the table, but it now seems unlikely that airlines will recommission operations equivalent to 90% of 2019 in the final quarter, and the analysis does not take into account new restrictions on inter-state travel in the US.

Our idea of what the traffic demand curve will look like post-Covid-19 is shown in the chart. (This and the following charts are not meant as reliable forecasts — Taleb has put us off — but as a framework within which to consider future trends.) In 2021, assuming no second-phase epidemics, the suggested global RPK growth rate is a remarkable 49%, the rebound being based on assuming that traffic the first half of that year will be 15% below 2019 and the second half at the same level as in 2019. A further 8% increase in 2022 would restore global traffic to the full year 2019 total.

At what rate will traffic “normalise” after the rebound? Looking at the long-term graphs, there is no consistent answer; traffic growth rates in various markets can be below or above pre-crisis rates. Long term trends do not miraculously recover lost passengers, rather the post -crisis growth trends are the result of structural changes that have taken place in the industry, and the crises frequently act as catalysts for structural change. So, for example, European traffic grew strongly after the September 11 crisis largely because of the emergence of LCCs; Asian traffic after the Financial Crash was sustained by the emergence of China and the Super-Connectors; modest North American traffic growth at the same time was largely the result of US major carriers’ restructuring and consolidation, trading expansion for profits.

It seems that in the post-Covid-19 world the structural changes will tend to depress the demand curve, and traffic will not get close to catching up with pre-Covid-19 expectations.

  • Business travel will be changed by Covid-19 isolation. It could have created a generation of Zoom executives, working effectively from home and communicating via videoconference, although many hate the isolation and get frustrated by the still clunky technology. In any case, corporations will be desperate to cut costs and travel budgets will be one of first items to be slashed.
  • Leisure travel is more difficult to call. There is undoubtedly huge pent-up desire for travel but how this will translate into demand depends on the damage done to personal balance sheets.
  • Airline costs should fall because of lower capital costs (ultra-low interest rates and oversupply of aircraft), labour costs (rationalising of operations), fuel costs (the collapse in oil prices minus losses on hedges), and if this translates into lower fares, there could be conceivably be some stimulus to traffic. On the other hand, most airlines appear to be determined to rein in capacity and cut expansion plans which will have the opposite effect on fares.
  • The anti-flying movement has been reinforced by the global grounding of aircraft. Suddenly NOx and carbon emissions have been radically reduced and noise pollution around major airports eliminated. There will be intense pressure for some of these environmental improvements to be retained after flights resume.

So we have plumped for an arbitrary 6% pa average growth rate post the rebound; it would take an average 15% pa growth rate to get back to the pre-Covid-19 trendline.

What all this means for the global supply/demand balance is illustrated in the chart. The supply line represents the global fleet of commercial passenger jets with the projection, which includes 2020, estimated from planned deliveries from the manufacturers minus retirements from the fleet (put at the historically high rate of 750 units a year). This was the industry’s expectation pre-Covid-19.

The lower line is the RPK forecast converted into average aircraft units (nominally 192 seats) under the assumption of “efficient” utilisation (82% load factors and 8.6 hours/day). The difference between the two lines is the surplus. 2020 is of course a disaster, but what is perhaps worrying is that the surplus persists through to 2024 at least with a surplus of around 4,000 units, roughly twice the OEMs’ annual expected output.

The surplus is theoretical because such projected gaps are always filled, one way or the other. The next graph shows the surplus being eroded bring the industry back into equilibrium in 2024, maybe 2023. Note that restoring equilibrium depends entirely on a flattening of the supply curve (unless there is a divine intervention on the demand side).

How this might be achieved in shown in the final graph — a combination of reduced deliveries and increased retirements. In this scenario the OEMs will have to cut deliveries by about 40% in total during 2020-23 — over 3,000 units or about $300bn in revenue. Retirements will have to average 1,000 units a year for at least three years, compared to around 600/year in the past decade.

It is highly unlikely that these changes will be made smoothly. Manufacturers, desperate for cashflow, will attempt to enforce delivery contracts. Airlines, equally desperate for cashflow, will defer deliveries and cancel contracts wherever possible. Lawyers will be examining break clauses where aircraft deliveries have been delayed — the MAX is the clearly the most vulnerable, but delays have also affected the A321, 777, 787, A330 and A350.

Then there is the reality of retirements. If aircraft are scrapped or parted-out then they are definitely taken out of supply, but parked aircraft, especially repossessions, may return to the market. It is possible that the Covid-19 crisis will create a stockpile of older but perfectly serviceable aircraft available for intrepid entrepreneurs to pick up at bargain prices. If the oil price remains very low these aircraft will become more attractive. And there will also be a surplus of pilots and mechanics looking for employment. It could be a classic combination for start-ups.

In the middle of Covid-19 mess sit the lessors, massively exposed — 33% of the global operating fleet, 50% of the orderbook — to precipitous falls in asset values. AVAC, the only one of the leading appraisal companies to focus on actual values as opposed to now-irrelevant fair market values, has downrated its aircraft valuations by 25-35%, and that is unlikely to be the bottom. There is pain on both sides: cancelling orders, as Avalon has just done, means losing deposits and PDPs while the airlines are queuing up to renegotiate leases and threatening to return aircraft early. Moreover, unlike the manufacturers, airlines and airports, lessors have no plausible state aid case.

The shock will be immense for the operating lessors. They have expanded consistently over the past 25 years and navigated September 11 and the Global Financial Crash with minimum casualties. But this period of history does not include, as Taleb might point out, the sudden implosion of GPA, then one of two giants in the aircraft leasing business, in 1992 — a Black Swan caused by a combination of unexpected adverse events and irrational expansion.

Boeing, Airbus and state aid

It is almost inevitable that the OEMs will receive some form of government support as the national interest/ security argument is just too politically powerful. Boeing asked for $60bn of aid for the entire aerospace industry before the full threat of the pandemic was apparent in the US. It has been offered $17bn from the federal government’s $2tr stimulus package, but appears reluctant to accept this as it would involve the state taking equity in the manufacturer. Airbus has not yet made an explicit request for aid, but has been in talks with its German and French government shareholders (22% of the total).

But should the OEMs receive state aid? Going back to Taleb’s contention that corporations must prepare for extreme events because they are inevitable as well as improbable, and the cost of preparation should be an integral part of a corporation’s financial planning, have Boeing and Airbus followed such a strategy?

The short answer is no. The cashflow for the two OEMs from 2012 to 2019 are summarised in the tables. Over the period 2012-19 Boeing generated $50.8bn in Free Cashflow (ie, after all operational flows and capital expenditure) but it then returned a total of $65.7bn to shareholders through dividends and share buy-backs. What this means is that Boeing has in effect being borrowing money, $14.9bn in total, to recycle to shareholders in order to support its share price; it slightly decreased its cash reserves over this period. It continued this financial strategy in 2019 despite the MAX crisis, leading Aviation Strategy to speculate wildly about state aid (November 2019) before anyone had heard of Covid-19. By the end of 2019 Boeing’s book value on its balance sheet had fallen to -$8.3bn.

Airbus has been doing more of less the same thing, but to a lesser extent. During 2012-19 Free Cashflow totalled €9.9bn while shareholders received €11.7bn in dividends and share buy-backs. It at least has maintained a positive value on the balance sheet, €6.0bn.

Yet from investors’ perspective the OEMs’ financial strategy looked like a success until this year — the OEMs’ share prices soared by a factor of six between 2012 and the beginning of 2019, and held up reasonably well during the MAX crisis. Indeed, the financial strategy largely reflects the pressure that has been put on equity markets to outperform as interest rates have maintained at ultra-low levels — it’s the only way a balanced portfolio can make a decent return. It had also almost obliged equity analysts to focus intently on quarterly performance, especially in the US, at the expense of longer term valuations.

A condition of government bailouts might be a regulatory requirement to hold certain levels of reserves or to limit dividends and share buy-backs to a certain percentage of Free Cashflow. This of course could introduce new distortions and have unintended consequences.

BOEING: CASHFLOW ITEMS
US$bn 2019 2018 2017 2016 2015 2014 2013 2012 Total 2012-19
Total Revenue 76.6 101.1 94.0 93.4 96.1 90.7 86.6 71.2 709.7
Net Result -0.6 10.5 8.4 5.0 5.2 5.4 4.6 3.9 42.4
Operating Cashflow -2.4 15.3 13.3 10.4 9.4 8.8 8.2 7.5 70.5
Capex/Net Investments -1.5 -4.6 -2.1 -3.4 -1.8 2.5 -5.1 -3.7 -19.7
Free Cashflow -3.9 10.7 11.2 7.0 7.6 11.3 3.1 3.8 50.8
Increase/Decrease in Debt 13.0 1.3 1.4 0.2 1.3 -0.4 0.1 -2.2 14.7
Share Buy Backs -2.7 -9.0 -9.3 -7.0 -6.7 -6.0 -2.8 0.0 -43.5
Dividends -4.6 -4.0 -3.4 -2.8 -2.5 -2.1 -1.5 -1.3 -22.2
Total financial Flows 5.7 -11.7 -11.3 -9.6 -7.9 -8.5 -4.2 -3.5 -51.0
Net Change in Cash 1.8 -1.0 -0.1 -2.6 -0.3 2.8 -1.1 0.3 -0.2
Cash Balance (end period) 9.6 7.9 8.9 9.0 11.6 11.9 9.1 10.3 9.8
Net Profit Margin -0.8% 10.4% 8.9% 5.4% 5.4% 6.0% 5.3% 5.5% 6.0%
Op. Cashflow Margin -3.1% 15.1% 14.1% 11.1% 9.8% 9.7% 9.5% 10.5% 9.9%
Capex/Investments as
% of Operating Cashflow -62.5% 30.1% 15.8% 32.7% 19.1% -28.4% 62.2% 49.3% 27.9%
Share Buy Backs/ Dividends
as % of FCF -187.2% 121.5% 113.4% 140.0% 121.1% 71.7% 138.7% 34.2% 129.3%
AIRBUS: CASHFLOW ITEMS
€bn 2019 2018 2017 2016 2015 2014 2013 2012 Total 2012-19
Total Revenue 70.5 63.7 59.0 66.5 64.5 60.7 57.8 56.5 499.2
Net Result -1.3 3.1 2.4 1.0 2.7 2.3 1.5 1.2 12.9
Operating Cashflow 3.8 2.3 4.4 4.4 2.9 2.6 1.8 3.8 26.0
Capex/Net Investments -2.9 -1.6 -2.5 -0.8 -3.5 -3.2 -1.6 0.0 -16.1
Free Cashflow 0.9 0.7 1.9 3.6 -0.6 -0.6 0.2 3.8 9.9
Increase/Decrease in Debt 0.3 -2.0 0.0 1.7 1.5 1.3 -0.6 3.6 5.8
Share Buy Backs 0.0 0.0 0.0 -0.8 -0.3 0.0 0.0 0.0 -1.1
Dividends -1.3 -1.2 -1.0 -1.0 -1.0 -0.6 -0.5 -4.0 -10.6
Total financial Flows -1.0 -3.2 -1.0 -0.1 0.2 0.7 -1.1 -0.4 -5.9
Net Change in Cash -0.1 -2.5 0.9 3.5 -0.4 0.1 -0.9 3.4 4.0
Cash Balance (end period) 9.3 9.4 11.9 11.0 7.5 7.9 7.8 8.7 9.2
Net Profit Margin -1.8% 4.9% 4.1% 1.5% 4.2% 3.8% 2.6% 2.1% 2.6%
Op. Cashflow Margin 5.4% 3.6% 7.5% 6.6% 4.5% 4.3% 3.1% 6.7% 5.2%
Capex/Investments as
% of Operating Cashflow 76.3% 69.6% 56.8% 18.2% 120.7% 123.1% 88.9% 0.0% 61.9%
Share Buy Backs/ Dividends
as % of FCF 144.4% 171.4% 52.6% 50.0% -216.7% -100.0% 250.0% 105.3% 118.2%
BOEING: BALANCE SHEET
($ Billions,End 2019)
Property and Plant 12.5
Intangibles (inc Goodwill) 12.6
Inventories 76.6
Cash etc 9.6
Other Assets 22.3
TOTAL ASSETS 133.6
Advances and PDPs 51.6
Accrued Liabilities 22.9
Pension/Health Plans 20.8
Accounts payable 15.6
Short-term debt 7.3
Long-term debt 23.4
Other 0.3
TOTAL LIABILITIES 141.9
EQUITY (DEFICIT) -8.3
AIRBUS: BALANCE SHEET
(€ Billions, End 2019)
Property and Plant 17.3
Intangibles (inc Goodwill) 16.6
Inventories 31.6
Cash etc 9.3
Other Assets 39.6
TOTAL ASSETS 114.4
Advances and PDPs 41.2
Other Short Term Liabilities 21.1
Pension Plans 8.3
Other Liabilities 12.6
Long term debt (inc Govt funding) 25.2
TOTAL LIABILITIES 108.4
EQUITY (DEFICIT) 6.0
CAPACITY AND YIELD ASSUMPTIONS
2020
Region of airline registration Q1 Q2 Q3 Q4
Capacity
Asia Pacific -18% -50% -25% -10%
North America -8% -50% -25% -10%
Europe -10% -90% -45% -10%
Middle East -23% -80% -40% -10%
Africa -10% -60% -30% -10%
Latin America -9% -80% -40% -10%
Industry -14% -65% -33% -10%
Passenger yield
Industry -8% -6% -4% -3%
Source: IATA
PRE-COVID PROJECTED JET DELIVERIES
BOEING AIRBUS OTHERS TOTAL
737 NG 737 MAX 747 767 777 787 Total A220 A320ceo A320neo A330 A330neo A350 A380 Total
2019 70 57 7 43 45 158 380 48 91 551 12 41 112 8 863 151 1,394
2020 40 236 10 30 55 140 511 60 66 656 20 50 124 9 985 184 1,680
2021 610 10 30 55 140 845 70 760 15 50 120 1,015 260 2,120
2022 650 10 30 70 140 900 70 730 15 60 110 985 310 2,195
2023 680 5 30 100 175 990 70 750 10 70 130 1,030 390 2,410
2024 540 5 30 120 155 850 60 590 10 50 100 810 350 2,010
2025 620 5 30 120 165 940 80 690 10 60 100 940 360 2,240
Source: Airline Monitor
TRAFFIC BY REGION THROUGH THE CRISES
Produced by GNUPLOT 5.5 patchlevel 0 0 500 1,000 1,500 2,000 2,500 1990 1995 2000 2005 2010 2015 2020 RPK bn RPKs RPKs NORTH AMERICAN AIRLINES 0 500 1,000 1,500 2,000 2,500 3,000 3,500 1990 1995 2000 2005 2010 2015 2020 RPK bn RPKs RPKs EUROPEAN AIRLINES 0 1,000 2,000 3,000 4,000 5,000 1990 1995 2000 2005 2010 2015 2020 RPK bn RPKs RPKs ASIAN AND MIDDLE EAST AIRLINES 0 2,000 4,000 6,000 8,000 10,000 12,000 1990 1995 2000 2005 2010 2015 2020 RPK bn RPKs RPKs WORLD AIRLINES

Sources: Airline Monitor, ICAO, IATA.

COVID-19 CRISIS AND POSSIBLE TRAFFIC RECOVERY
Produced by GNUPLOT 5.5 patchlevel 0 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 -60% -40% -20% 0% 20% 40% 60% Annual Change Global RPKs (bn) Pre Covid-19 Projection Annual Change Global RPKs (bn) Pre Covid-19 Projection
GLOBAL JET AIRCRAFT MARKET:
Theoretical Surplus c4,000 Units Until 2024
Produced by GNUPLOT 5.5 patchlevel 0 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 Jets in fleet annual average Global Commercial\nPax Jet Fleet Projection - Planned Deliveries\n minus “Normal” Retirements Demand based on\nRPK Projection Theoretical Surplus Global Commercial Pax Jet Fleet Projection - Planned Deliveries minus “Normal” Retirements Demand based on RPK Projection Theoretical Surplus
CRUDE OIL AND JET KEROSENE
Produced by GNUPLOT 5.5 patchlevel 0 0 20 40 60 80 100 120 140 2012 2013 2014 2015 2016 2017 2018 2019 2020 US$/bbl Brent Crude Jet Kerosene Brent Crude Jet Kerosene

Source: EIA

GLOBAL JET AIRCRAFT MARKET: TO RESTORE EQUILIBRIUM
Three years of peak retirements and 40% reduction in deliveries to 2024
Produced by GNUPLOT 5.5 patchlevel 0 -1,500 -1,000 -500 0 500 1,000 1,500 2,000 2,500 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 OEMs' Lost Deliveries Pre Covid 19 Deliveries Covid Reduced\nDeliveries Historical Retirements Covid Increased\nRetirements Pre Covid 19 Deliveries OEMs' Lost Deliveries Pre Covid 19 Deliveries Covid Reduced Deliveries Historical Retirements Covid Increased Retirements
GLOBAL JET AIRCRAFT MARKET:
Elimination of Surplus by 2023/24
through increased retirements and reduced deliveries
Produced by GNUPLOT 5.5 patchlevel 0 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 Jets in fleet annual average Global Commercial\nPax Jet Fleet Projection - Reduced deliveries\n minus accelerated Retirements Demand based on\nRPK Projection Theoretical Surplus Global Commercial Pax Jet Fleet Projection - Reduced deliveries minus accelerated Retirements Demand based on RPK Projection Theoretical Surplus
OEM SHARE PRICE PERFORMANCE
Produced by GNUPLOT 5.5 patchlevel 0 100 200 300 400 500 600 700 800 2012 2013 2014 2015 2016 2017 2018 2019 2020 Indexed (Jan 2012=100) Boeing Airbus Boeing Airbus
……

This is premium content, only available to subscribers.
To access Login or contact info@aviationstrategy.aero

×